In 1948, Claude Shannon initially proposed his famous “noisy channel encoding theory” which firstly defines the maximum transmission rate of the noisy channel information, i.e., channel capacity. Meanwhile, Shannon also derived the limited transmission capability of the noisy channel, i.e., the minimum Signal-to-Noise Ratio required by errorless information transmission, which is also called as Shannon limit. The Shannon limit is an important indicator for evaluating the channel error correction capability. The closer the error correction performance curve to the Shannon limit, the more excellent is the error correction performance. Otherwise, farther to the Shannon limit, the worse is the performance.
The Low Density Parity Code (LDPC) is a kind of excellent channel error correction encoding scheme which may approach the Shannon limit. The LDPC code is a special linear parity check block code, whose parity check matrix is “sparse”: there is only very few non-zero matrix elements (for the binary code, non-zero element is 1), and the remaining elements are all zero. In 1960, Robert Gallager firstly proposed the concept of LDPC code in his Ph.D. dissertation and also suggested two iterative decoding algorithms, thus the LDPC code is also called as Gallager code. Gallager indicated theoretically that the LDPC code may approach the channel capacity with lower complexity by using iterative decoding algorithms (or message delivering algorithms). This is a great invention, however, in the following 30 years researchers did not pay enough attention to the invention.
From the current viewpoint, one reasons why the LDPC code was ignored might consist in that the software and hardware levels of the computers were underdeveloped at that time, and thus the researches could not know the excellent performance of the LDPC code from results of computer simulations; as another reason, the LDPC code needs a larger storage space which could not be achieved at that time. Additionally, at that time, other codes such as Reed-Solomon code and Hamming code were available, which might be considered as temporarily usable channel encoding schemes, and thus the researchers did not intently forward their researches onto the LDPC code.
Even today, if it is intended to apply the LDPC code to actual communication systems, the LDPC code still needs to be carefully studied and designed. Since LDPC code has some special requirements when applying to actual communication systems, such as codec hardware schemes having lower complexity, excellent error correction performance, and the like, it is required to specially limit the construction of the parity check matrix of the LDPC code as well as deeply study on the encoding/decoding method. Generally, there are two methods of constructing the parity check matrix of the LDPC code: one is to firstly set some attribute limitations on the parity check matrix such as minimum girth or node degree distribution and then randomly or pseudo-randomly generate the parity check matrix by using the computer searching methods; the other is to construct the parity check matrix of the LDPC code by using the mathematical formulae to make it have regular structure.
Mobile digital multimedia broadcast communication system is developing rapidly in recent years, and a normal system thereof is termed as “Mobile TV” system. The most difficult part in the design of the mobile TV system lies in the miniaturization of the mobile phone and low power consumption design. Therefore, the technology adopted by the system normally has a high performance with low complexity, such as channel encoding technology.
The LDPC proposed in the present invention is a channel encoding scheme applicable to the mobile digital multimedia broadcast communication system.